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本指南将帮助你开始使用 Perplexity chat models。有关所有 ChatPerplexity 功能和配置的详细文档,请前往 API 参考

概述

集成详情

ClassPackageSerializablePY supportDownloadsVersion
ChatPerplexity@langchain/communitybetaNPM - DownloadsNPM - Version

模型功能

请参阅下表标题中的链接,了解如何使用特定功能。 Note that at the time of writing, Perplexity only supports structured outputs on certain usage tiers.

设置

要访问 Perplexity models,你需要create a Perplexity account, get an API key, and install the @langchain/community integration package.

凭证

前往 https://perplexity.ai 注册 Perplexity 并生成 API 密钥。完成后设置 PERPLEXITY_API_KEY 环境变量:
export PERPLEXITY_API_KEY="your-api-key"
如果你想要自动追踪模型调用,还可以设置你的 LangSmith API 密钥,取消注释以下内容:
# export LANGSMITH_TRACING="true"
# export LANGSMITH_API_KEY="your-api-key"

安装

LangChain 的 Perplexity 集成位于 @langchain/community 包中:
npm install @langchain/community @langchain/core

实例化

现在我们可以实例化模型对象并生成聊天补全:
import { ChatPerplexity } from "@langchain/community/chat_models/perplexity"

const llm = new ChatPerplexity({
  model: "sonar",
  temperature: 0,
  maxTokens: undefined,
  timeout: undefined,
  maxRetries: 2,
  // 其他参数...
})

调用

const aiMsg = await llm.invoke([
  {
    role: "system",
    content: "You are a helpful assistant that translates English to French. Translate the user sentence.",
  },
  {
    role: "user",
    content: "I love programming.",
  },
])
aiMsg
AIMessage {
  "id": "run-71853938-aa30-4861-9019-f12323c09f9a",
  "content": "J'adore la programmation.",
  "additional_kwargs": {
    "citations": [
      "https://careersatagoda.com/blog/why-we-love-programming/",
      "https://henrikwarne.com/2012/06/02/why-i-love-coding/",
      "https://forum.freecodecamp.org/t/i-love-programming-but/497502",
      "https://ilovecoding.org",
      "https://thecodinglove.com"
    ]
  },
  "response_metadata": {
    "tokenUsage": {
      "promptTokens": 20,
      "completionTokens": 9,
      "totalTokens": 29
    }
  },
  "tool_calls": [],
  "invalid_tool_calls": []
}
console.log(aiMsg.content)
J'adore la programmation.

API 参考

有关所有 ChatPerplexity 功能和配置的详细文档,请前往 API 参考